English  |  正體中文  |  简体中文  |  Items with full text/Total items : 65317/65317 (100%)
Visitors : 21315530      Online Users : 194
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/7743


    Title: 用卜瓦松與負二項分配建構非負連續隨機變數平均數之概似函數;Building likelihood function for non-negative continuous random variates using Poisson and negative binomial odels.
    Authors: 戴名祥;Ming-Shiang Dai
    Contributors: 統計研究所
    Keywords: 強韌概似函數;卜瓦松分配;負二項分配;Poisson distribution;robust likelihood function;negative binomial distribution
    Date: 2009-06-03
    Issue Date: 2009-09-22 11:03:44 (UTC+8)
    Publisher: 國立中央大學圖書館
    Abstract: 當我們分析一筆資料時,常常會根據資料的型態,對資料作參數模型的假設,但是當模型假設錯誤時,分析的結果會有錯誤。本文在Royall and Tsou (2003)的強韌概似函數理念下,針對不同類型的非負連續資料,以離散型分配卜瓦松與負二項的強韌概似函數提供正確的統計推論。經由模擬發現,這兩類模型表現比連續型分配的常態強韌概似函數好,而在一些情況下,表現不比連續型伽瑪強韌概似函數與逆高斯強韌概似函數差。文中也以不適合強韌化的連續型對數常態分配作為反例,說明可強韌化條件(Royall and Tsou, 2003)的重要。 The purpose of this research is trying to use discrete distribution to construct a likelihood function for non-negative continuous data. We focus on the Poisson distribution and negative binomial distribution and use the robust likelihood methodology introduced by Royall and Tsou (2003). Finally, we can see that the robust Poisson model and the robust negative binomial model are more efficient than the robust normal model. Moreover, we use a counter-example to illustrate that it is not coincidental.
    Appears in Collections:[統計研究所] 博碩士論文

    Files in This Item:

    File SizeFormat
    0KbUnknown749View/Open


    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback  - 隱私權政策聲明